A probabilistic algorithm to process geolocation data.
A probabilistic algorithm to process geolocation data.
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DOI：
10.1186/s40462-016-0091-8
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发表时间：
2016
期刊：
影响因子：
4.1
通讯作者：
Strøm H
中科院分区：
文献类型：
--
作者：
Merkel B;Phillips RA;Descamps S;Yoccoz NG;Moe B;Strøm H
近年来，使用光照记录仪（地理定位仪）来了解陆地和海洋脊椎动物的运动和分布，特别是在非繁殖期，已经急剧增加。然而，从光数据推断位置并不简单，往往依赖于难以检验的假设，或者包含主观因素。我们提出了一个直观的框架，从不同制造商的地理定位器收集的暮光事件中计算位置。该过程使用迭代的前向步骤选择，使用一组可为每个分析具体选择的参数对每个可能的位置进行加权。该方法在两种分布广泛的海鸟物种——黑眉信天翁（Thalassarche melanophris）和漫游信天翁（Diomedea exulans）——的数据上进行了测试，这两种海鸟在南乔治亚岛的鸟岛被追踪到，时间是一年中光照状况最不一致的两个时期（至日和春分）。利用额外的旅行速度、海面温度和陆地回避信息，我们的方法比传统的阈值方法要准确得多（误差分别减少到至日和春分期间的中位数185公里和145公里）。该算法计算不确定性估计的稳定结果，包括在春分附近，并且不需要校准太阳角度。通过吸收有关旅行速度和行为的信息以及环境数据，可以提高准确性。这个框架可以通过开源R包probGLS获得，并且可以广泛应用于生物学研究。本文的在线版本（doi:10.1186/s40462-016-0091-8）包含补充材料，可供授权用户使用。
The use of light level loggers (geolocators) to understand movements and distributions in terrestrial and marine vertebrates, particularly during the non-breeding period, has increased dramatically in recent years. However, inferring positions from light data is not straightforward, often relies on assumptions that are difficult to test, or includes an element of subjectivity. We present an intuitive framework to compute locations from twilight events collected by geolocators from different manufacturers. The procedure uses an iterative forward step selection, weighting each possible position using a set of parameters that can be specifically selected for each analysis. The approach was tested on data from two wide-ranging seabird species - black-browed albatross Thalassarche melanophris and wandering albatross Diomedea exulans – tracked at Bird Island, South Georgia, during the two most contrasting periods of the year in terms of light regimes (solstice and equinox). Using additional information on travel speed, sea surface temperature and land avoidance, our approach was considerably more accurate than the traditional threshold method (errors reduced to medians of 185 km and 145 km for solstice and equinox periods, respectively). The algorithm computes stable results with uncertainty estimates, including around the equinoxes, and does not require calibration of solar angles. Accuracy can be increased by assimilating information on travel speed and behaviour, as well as environmental data. This framework is available through the open source R package probGLS, and can be applied in a wide range of biologging studies. The online version of this article (doi:10.1186/s40462-016-0091-8) contains supplementary material, which is available to authorized users.
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影响因子：
10.3
作者：
Fort, Jerome;Pettex, Emeline;Gremillet, David
通讯作者：
Gremillet, David
影响因子：
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Mosbech, Anders;Johansen, Kasper L.;Fort, Jerome
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Fort, Jerome
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影响因子：
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作者：
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通讯作者：
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